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Apache Spark™ - Unified Engine for Large-Scale Data Analytics

Apache Spark™ is a multi-language engine designed for executing data engineering, data science, and machine learning tasks on both single-node machines and clusters. It provides a unified framework that allows for the processing of batch and real-time streaming data. With support for multiple programming languages including Python, SQL, Scala, Java, and R, Apache Spark is widely adopted across industries for its speed and scalability.

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FAQs

What is Apache Spark?

Apache Spark is a unified engine for large-scale data analytics that supports data engineering, data science, and machine learning across single-node machines and clusters.

What programming languages does Apache Spark support?

Apache Spark supports multiple programming languages including Python, SQL, Scala, Java, and R.

What are the key features of Apache Spark?

Key features of Apache Spark include batch and streaming data processing, fast distributed ANSI SQL queries, data science at scale, and machine learning capabilities.

How does Apache Spark compare to traditional data warehouses?

Apache Spark runs faster than most data warehouses, enabling quick execution of complex queries for dashboarding and ad-hoc reporting.

What is the community like around Apache Spark?

Apache Spark has a thriving open-source community with over 2,000 contributors from industry and academia, actively building features, documentation, and supporting users.

Q: How often does Spark experience outages?

A: Major outages are rare, occurring only a few times a year. Minor issues can happen more frequently.

Q: How long do Spark outages typically last?

A: Most outages are resolved within a few hours. Extended outages lasting more than a day are extremely rare.

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